Abstract

The accuracy of radiopharmaceutical absorbed dose distributions computed through Monte Carlo (MC) simulations is mostly limited by the low spatial resolution of 3D imaging techniques used to define the simulation geometry. This issue also persists with the implementation of realistic hybrid models built using polygonal mesh and/or NURBS as they require to be simulated in their voxel form in order to reduce computation times. The existing trade-off between voxel size and simulation speed leads on one side, in an overestimation of the size of small radiosensitive structures such as the skin or hollow organs walls and, on the other, to unnecessarily detailed voxelization of large, homogeneous structures.We developed a set of computational tools based on VTK and Geant4 in order to build multi-resolution organ models. Our aim is to use different voxel sizes to represent anatomical regions of different clinical relevance: the MC implementation of these models is expected to improve spatial resolution in specific anatomical structures without significantly affecting simulation speed. Here we present the tools developed through a proof of principle example. Our approach is validated against the standard Geant4 technique for the simulation of voxel geometries.